• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.3
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• pp.275-288
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• 2010

In order to improve the quality of electricity in large scale power systems, stability of power system has to be achieved. This can be done by the means of preventative diagnosis of power equipments and protection, monitoring and control of the power system. Since the recent adoption of digital controllers, an improvement in stability was observed; in particular, IED, which contained self-diagnostic abilities such as fault tolerance, allowed for automatic recovery via redundancy or switching-over functions should there be faults with the equipments. Furthermore, communication lines have been hugely simplified, thus adding to the improvement in stability significantly. Taking these error reports and forecasting emergency reports and by effectively responding to them in the overiding controlling systems, high levels of system stability can be obtained. Power Management System that is being applied to automated power sub-stations, takes the IEC61850 international standard as its specification. In this paper, additional research into achieving stability of already developed PMS system and also the stability of the overall system was carried out, and the results of development of communication servers, which play a pivotal role in connecting systems, are stated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.6
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• pp.497-502
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• 2014

In general, all physicians have some standardized diagnosis and treatment methods. However, there are differences in the precise order and examination depending on the hospital size, system, medical equipment, etc. To reduce this difference, the interest about standardized guidelines recently increased and a variety of research is being conducted. The uniform guideline cannot reflect the differences of each situation and environment to meet the hospitals. Therefore, standardized medical guidelines(=clinical pathway) should provide customized guidelines based on the relevant medical data to ensure the quality of the medical service and the doctor's autonomy. In this paper, we will analyze medical data made by two thyroid specialists in the same hospitals. Moreover, this paper mentions the implement of automatic generating clinical pathway system which consider its real hospital situation and result.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.399-402
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• 2005

For efficient and accurate diagnosis of ultrasound images, the time gain compensation (TGC) and dynamic range (DR) control of the ultrasound echo signal are important. TGC is for compensating the attenuation of the ultrasound echo signal along the depth, and DR is used to control the image contrast. In this paper, we propose an algorithm for finding the optimized values of TGC and DR automatically. For TGC, the degree of compensation is determined along the depth based on the effective attenuation estimation of ultrasound signal. For DR optimization, we introduce a novel cost function on the basis of the characteristics of ultrasound image, which provides the minimum value at the optimal DR. Experiments have been performed by applying the proposed algorithm to a real US imaging system. The results show that the algorithm automatically can determine the values of TGC and DR in realtime so that the subjective quality of the corresponding US image may be good enough for diagnosis.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.269-272
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• 2000

It is need to develop and apply a human pulse diagnosis system providing a quantitative and automatic analysis in the the oriental medicine. In order to analyze quantitatively the characteristic of pulsation, each of points had to be recognized accurately notifying the existence and the position of feature point in the wave form. And getting the period of human pulse. Thus, in this paper, it is proposed the preprocessing method of human pulse and the detection method of period by Wavelet Transformation. The human pulse is seprated from each band through Wavelet Transformation and feature points can be recognized through over the fact, and then the parameter of proposed Mac-Jin parameter is measured. Commonly, Human pulse signal has often various noises which are baseline drift, high frequency noise and so on. So it is significant to remove that noises. Thus, in this paper, the one period of human pulse is deciede and the feature points are detected after doing the preprocessing by wavelet transformation. As a result, it could be confirmed that this method is effective as a real program for the auto-diagnosis of human pulse.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.362-369
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• 2014

This study aimed to propose an accurate diagnostic method for osteoporosis by realizing a computer-aided diagnosis system with the application of the statistical analysis of texture features using digital images of lateral lumbar spine of patients with osteoporosis and providing reliable supplementary diagnostic information by model experimental research for early diagnosis of diseases. For these purposes, digital images of lateral lumbar spine of normal individuals and patients with osteoporosis were used in the experiments, and the values of statistical texture features on the set ROI were expressed in six parameters. Among the texture feature values of the six parameters of osteoporosis, the highest and lowest recognition rates of 95 and 80% were shown in average gray level and uniformity, respectively. Moreover, all the six parameters showed recognition rates of over 80% for osteoporosis: 82.5% in average contrast, 90% in smoothness, 87.5% in skewness, and 87.5% in entropy. Therefore, if a program developing into a computer-aided diagnosis system for medical images is coded based on the results of this study, it is considered possible to be applied to preliminary diagnostic data for automatic detection of lesions and disease diagnosis using medical images, to provide information for definite diagnosis of diseases, to diagnose by limited device, and to be used to shorten the time to analyze medical images.

• Journal of Veterinary Clinics
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• v.14 no.2
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• pp.301-307
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• 1997

These studies were performed to provide some basic informations for developing an automatic system in dairy farming cattle in order that the farmers may easily and automatically detect the maintenance of pregnancy and the fact of abortion of the pregnant cows and also to find out the diseased animals with fever. As a method of automatical detection of the maintenance of pregnancy or the fact of abortion, weighing the pregnant cows was conducted from one month-pregnancy to the term using a digital balance. From the first to the 3rd month of pregnancy the body weight of dairy cows was slowly increased (less than 2% per month), then, relatively high increase (3.4% -4.3% per month) from the fourth to the seventh month followed by decrease (3.3%) in the 8th month and very low increase (0.8-0.9%) from the 9th month to the term were shown, resulting in increase of 128.8 kg (25.05%) of body weight to be compared with the first weight. More than 107, increase of body weight to be compared with the first month-weight was denoted from the 61th month of pregnancy and more than 20% increase from the 7th or the 8th month of pregnancy as wells consequently it was presumed that detection of the maintenance of pregnancy is possible from the 4th or the 5th month of pregnancy. It was possible to diagnose a cow aborted at the 6th month by continual weighing the cow from the 1st month of pregnancy. The calved cows showed considerably higher decrease of body weight even in the third week after parturition (p<0.01)to be compared with the body weight near to the term (81.8-102.0 kg, 14-16% decrease). During the same period of 8months, the pregnant cows gained 127.4 kg (24.78% increase), whereas the non-pregnant cows gained 33.0 kg (0.71% increase) to be compared with the first weight showing considerably higher increase of body weight gain in the pregnant cows than the non-pregnant cows (p<0.01). The statistics of body temperatures of dairy cattle were collected from three clinics including the Teaching Hospital of Chonbuk University and the diseases were classified simply by the major symptoms manifested, denoting the highest temperature in respiratory disease ($39.8{\circ}C$) and the lowest in alimentary disease ($39.6{\circ} C$). These informations of body temperatures were expected to be of value for early and automatical detection of the diseased animals with fever when automatic machinery would be established. The results of periodic weighing the body weight of pregnant cows while milking were also expected to be of great use for the farmers to detect the maintenance of pregnancy and the fact of abortion when the automatic system is established in the near future.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.403-414
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• 1995

It is very difficult to quantize the ECG analysis because the decision criterion for ECG is different with each other depending on the medical specialists of the heart and there are measured detecting errors for each ECG measurement system. Therefore, we developed the real-time ECG identification system using digital fuzzy processor for STD-BUS, in order to reduce ambiguity generated in the process of ECG identification and to analyze the irregular ECG stastically to ECG's repetition interval. The variables such as AGE (months), width of QRS, average RRI, and RRI were used to classify the ECG, and were applied to ECG signal indentification system which is developed for the purpose of research. It was found that the automatic diagnosis of ECG signal was possible in the real time process which was impossible in general process of algorithm.

• Journal of Biomedical Engineering Research
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• v.16 no.1
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• pp.107-113
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• 1995

It is well known that multipoint and computerized intraoperative mapping systems improve the results of surgery for Wolff-Parkinson-White syndrome and show tremendous potential for opening an entirely new era of surgical intervention for the more common and lethal types of supraventricular tachyarrhythmias such as atrial flutter and atrial fibrillation. In addition, the ability to map and ablate the sometimes fleeting automatic atrial tachycardia is greatly enhanced by computerized mapping systems. In this study, we have developed 64 channel computerized data analysis system using microcomputer (Macintosh ${II}_{x}$) for basic research of electrophysiology and electrical propagation. The bipolar electrogram information is acquired from 64 cardiac sites simultaneously at a sampling rate of 1 ksampls/sec with continuous and total data storage of up to 30 seconds. When the reference electrogram is selected and reference point is picked up, delay time from the reference point is displayed on two dimensional diagram of the heart. System design permits easy expansion to almost 256 simultaneous sites. this system is expected to enable us to study pathophysiology of cardiac arrhythmia and to improve the result of diagnosis and surgical treatment for cardiac arrhythmia.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.92-95
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• 2019

Automation control and the data for control of industrial equipment for the diagnosis and prediction is a key to success in the 4th industrial revolution. It increases process efficiency and productivity through data collection, realtime monitoring, and the data analysis. However, university and research environment are still suffering from logging the data in manual way, and we occasionally loss the equipment data logging due to the lack of automatic data logging system. State variable presents the current condition of the equipment operation which is closely related to process result, and it is valuable to monitor and analyze the data for the equipment health monitoring. In this paper, we demonstrate the collection of equipment state variable data via programmable logic controller (PLC) and the visualization of the collected data over the Web access supervisory control and data acquisition (SCADA). Test vehicle for the implementation of the suggested SCADA system is a relay switched physical vapor deposition system in the university environment.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.241-243
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• 2003

일반적으로 사용되는 반도체 공정에 대한 진단 기법은 한 공정을 진행하기 전에 테스트 공정을 수행하여 공정의 진행 여부를 결정하고, 한 공정의 진행을 완료한 후에 다시 테스트 공정을 수행하여 공정의 결과를 진단하는 방법이다. 본 논문에서 제안하는 실시간 자동 진단 시스템은 기존 방법의 문제점인 자원의 낭비를 막고, 실시간으로 진단함으로써 시간의 낭비를 막는 진단 시스템을 제안한다. 실시간 자동 진단 시스템은 크게 시스템 초기화 단계, 학습 단계 그리고 예측 단계로 나누어진다. 초기화 단계는 진단할 공정에 대한 사전 입력값을 받아 시스템을 초기화하는 과정으로 공정장비 파라미터별 중요도 자동 설정 과정과 초기화 클러스터링으로 이루어진다. 학습 단계는 실시간으로 저장된 공정장치별 데이터와 계측기로부터 획득된 데이터를 이용하여 최적의 유사 클래스를 결정하는 단계와 결정된 유사 클래스를 이용하여 가중치를 학습하는 단계로 나누어진다. 예측 단계는 공정 진행 중 획득된 실시간 데이터를 학습 단계에서 결정된 파라미터별 가중치를 사용하여 공정에 대한 진단을 한다. 본 시스템에서 사용하는 클러스터링 알고리즘은 DTW(Dynamic Time Warping)를 이용하여 파라미터 데이터에 대한 특징을 추출하고 LBG(Linde, Buzo and Gray) 알고리즘을 사용하여 데이터를 군집화 한다.